Figure 5.

CTMM accuracy at the population level. A, Mean error t-score (across neurons) at each moment in time after the ETOC was quantified as a t-score (a larger score is worse). The CTMM error (green) is much lower than that of the additive prediction (gray) throughout the multisensory response, but particularly within the IRE (gray box), where multisensory enhancement was greatest. A, Inset, SEM t-score for the CTMM was also lower than that of the additive model throughout most of the response, indicating that CTMM more precisely captured the variation within the population. B, Percentage of CTMM predictions (green) and additive predictions (gray) across the population that are “practically equivalent” (i.e., not statistically distinguishable) from the actual multisensory response at each moment in time. Note the high effectiveness of the CTMM predictions, especially during the IRE, where the performance of the additive model is particularly poor. C, Bias of the CTMM (green) and additive prediction (gray) at each moment in time indicate when either model prediction of the multisensory response was consistently too high (positive) or too low (negative). The CTMM predictions varied around 0. However, the additive model underestimated the magnitude of the multisensory response significantly during the IRE. D, By regressing the total error of each model's predictions against the sum of the total unisensory magnitudes, a pattern of errors was noted for the additive prediction (gray) that changed as the magnitude of the multisensory response changed. Such a pattern of errors was not present in the CTMM predictions.